A Systematic Review of GIS-Driven Road Traffic Accident Evaluation

The review has explored the application of Geographic Information Systems (GIS) in evaluating road traffic crashes, stressing its role in identifying crash spatial patterns and hotspots. GIS offers a framework for integrating spatial and non-spatial data, allowing scholars and planners to visualize crash-prone areas and understand their distribution. A total of 77 research articles from the publication period of 2010–2025 were included for final reviews. A Systematic Reviews and Meta-Analyses (PRISMA) approach is followed to provide well-structured, transparent, and standardized information on articles. The intention is to assess how different GIS techniques contribute to road safety analysis and to the development of effective intervention strategies. The review focused particularly on four key GIS-based spatial analysis methods: Kernel Density Estimation (KDE), Network KDE, Moran’s I (Global and Local), and Getis-Ord Gi*. Among these, KDE and Moran’s I were the most frequently adopted techniques, covering about 31.17% and 23.38% of reviewed articles, respectively. These techniques are essential for identifying statistically significant clusters and crash concentration. Despite their promising results, the studies also reveal limitations, including inconsistent data quality, high computational demands, and limited use of variables such as road geometry characteristics. Although GIS is an effective tool for planning and analyzing road safety, these deficiencies might be addressed by future studies that advance the use of real-time spatial analytics and incorporate more diversified information. Overall, the review has reinforced the critical role of GIS in improving traffic safety through real-time data-driven interventions.